The application's broad, long-term objective is to reduce the disease burden of breast cancer through early detection and accurate diagnosis, which lead to effective treatment. The goal of this project is to develop innovative approaches to computer-aided diagnosis (CADx) of breast calcifications for breast cancer detection and diagnosis. Other researchers in our group are developing CADx for breast masses separately, in conjunction with this project, because diagnostic workup of breast masses requires multi-modality imaging (ultrasound and MRI) in addition to mammography. We will test the hypothesis that CADx of breast calcifications can help improve breast cancer detection and diagnosis. The Specific Aims of this project are: (1) reduce or eliminate influence on computer classification from inter- and intra-radiologist variability in their interaction with the computer; (2) investigate computer classification of magnification mammogram; (3) investigate and reduce computer variability in classification of a lesion in multiple views; and (4) investigate potential benefit of CADx to enhance the effectiveness of computer-aided detection (CADe) in screening mammography. The research design will be to understand the mechanisms of computer variability in its calculations from the identified sources, to develop new techniques to minimize computer calculation variability, to develop new techniques for new CADx applications, and to perform an observer performance study to show that CADx can potentially enhance the effectiveness of CADe. The methods to be used include computer image analysis, statistical classifier, ROC analysis, statistical comparison, and observer performance study. The rationales for pursuing these goals include an anticipated need to address critical clinical acceptance issues of CADx based on already demonstrated high performance of our CADx technique and a planned pre-clinical and clinical evaluation of CADx, and a new opportunity for potential novel application of CADx to enhance the effectiveness of CADe. The techniques that we will use are either proven in previous investigations, or based on theoretical studies, or based on our observation in working with radiologists developing CADx techniques. The importance and health relatedness of the research described in this application is that it will address significant limitations of current CADx technique that likely will hinder clinical acceptance of CADx and will address an innovative potential for CADx to enhance the effectiveness of CADe in breast cancer detection. If the Aims of the application are achieved, CADx will be advanced technologically and will become more clinically acceptable to radiologists: once clinical benefit of CADx is demonstrated, CADx will become an important new clinical tool for breast cancer detection and diagnosis.